R&D Senior Product Owner Data Governance and Semantics
Pubblicato il 15-10-2026 - Chiesi in Terni
Overview As part of Chiesi’s R&D; transformation, you will lead the data governance and semantics effort to maximize R&D; data value. You will shape the semantic layer, metadata, and knowledge graph to enable trusted, discoverable data and AI-driven insights. You’ll collaborate with SMEs and IT to enforce governance and quality, driving a data-driven culture across R&D.; This role offers visibility across clinical and GICT domains and a meaningful impact on research productivity and compliance. Retribuzione / Benefits * annual premio scheme * pension * private medical insurance * wellbeing programme * flexible benefits programme * remote working Responsabilità * Lead semantic layer, data model, and ontologies to unify the R&D; data ecosystem with a focus on clinical data domains * Architect a knowledge graph integrating heterogeneous R&D; data * Ensure linked metadata and machine-readable glossaries for advanced data discovery and AI insights * Develop and implement a comprehensive R&D; data governance framework * Define data stewardship policies, roles,
and quality rules in line with governance policies * Collaborate with functional SMEs to ensure data is defined and maintained per guidelines * Promote ALCOA+/FAIR principles across data management * Define product requirements, backlog, and roadmap for data sets delivered by engineering * Monitor data quality KPIs and usage metrics; iterate on enhancements * Establish data quality frameworks with validation rules, profiling, and anomaly detection * Engage stakeholders and communicate governance value; mentor and balance priorities * Establish metrics to track governance effectiveness and drive continuous improvement Requisiti fondamentali * Advanced degree (Master’s/PhD) in Life Sciences, Data Science, or related field * Minimum 5 years in R&D; clinical domain * Minimum 3 years in a Product Owner or similar strategic role with backlog management * Strong background in data modeling techniques * Experience in Pharmaceutical